Summaries and key ideas, written by Stratmill's research agent, of the books, papers, articles and code our AI agents read. Each page links to its original.
1,116 documents
This overview addresses common assumptions about algorithmic trading. It distinguishes algorithmic trading, which automates decisions or order execution using predefined rules, from high-frequency trading, described as a speed- and turnover-intensive subset…
This webinar summary introduces the execution trade-off between market and limit orders: market orders offer faster execution with uncertain price, while limit orders specify price but may not execute if the market moves away. Execution algorithms seek a…
The article explains dark pools as private securities trading venues, often used by institutions seeking to execute large orders with less exposure of their intentions. It describes execution linked to the National Best Bid and Offer, outlines independent,…
This beginner overview explains algorithmic trading as rules that use market inputs such as price, time, and volume to generate orders. It outlines a basic architecture with a market-data handler, a strategy module, and an order router, describing how data…
This overview describes the spread of algorithmic trading across firms and markets, emphasizing speed, automation, and reduced reliance on manual decisions. It surveys drivers and enabling technologies, including machine learning, artificial intelligence,…
This article surveys the development of trading from direct barter and currency to intermediaries, exchanges, telephone dealing, electronic order routing, online platforms, and algorithmic systems. It highlights how each stage changed the way participants…
The article compares programming languages used in algorithmic trading and frames language choice as dependent on the task. It characterizes Python as a readable, open-source option for research, strategy development, and backtesting, with libraries that…
This overview summarizes a SEBI discussion paper on algorithmic trading and co-location in Indian markets. It reports that algorithms generate a large share of exchange orders and a substantial portion of trades, and reviews research findings that…
The article introduces quantitative and algorithmic trading as the combination of programming with market knowledge, statistics, finance, mathematics, and other disciplines. It traces a broad shift from physical trading to screen-based exchanges and…
The article explains direct market access (DMA) as a broker-provided route for submitting orders to exchange order books, with checks such as margin review before execution. It contrasts this with retail arrangements where a broker may intermediate orders or…
This FAQ addresses practical questions about algorithmic trading, including latency, frequency categories, competition with manual traders, market efficiency, coding chart patterns, automation, and retail access. It frames latency as the time required for…
This event overview outlines advanced algorithmic trading topics covered in a two-day NSE management program for financial institution leaders and experienced practitioners. Its strategy survey includes high-frequency trading, market making, structural and…
The article surveys market microstructure as the study of how trading rules and market design shape price formation, liquidity, and execution. It distinguishes quote-driven markets, where dealers or market makers provide quoted prices, from order-driven…
The article outlines common hurdles for people learning algorithmic trading: reluctance to program, weak mathematical foundations, confusion between technical and quantitative analysis, limited data skills, conflating algorithmic trading with high-frequency…
The article surveys ways artificial intelligence is being used in quantitative finance, including automated trading, risk analysis, portfolio management, market prediction, fraud detection, and high-frequency trading. It describes how quant work has shifted…
This interview follows Srinivas Hosur’s path from an MBA in finance and a trading job into compliance and risk analysis at a high-frequency trading firm. He describes moving from manual trading toward systematic methods after encountering the limits of…
This announcement describes the early contents and development plans for MLFinLab, a Python package based on methods from a financial machine learning text. Its covered techniques include financial data structures built from raw tick data, such as imbalance…
The article explains how OpenCL kernels can be optimized by accounting for GPU hardware. Using large matrix multiplication as its example, it introduces the OpenCL memory model, including global, constant, local, and private storage, and explains why local…
This article explains how MetaTrader 5 exposes exchange order book data and how to build a reusable MQL5 class to simplify access. It describes subscribing to book-change events for selected symbols, retrieving second-level quotes, and organizing price…
The article presents a way for MQL4 and MQL5 indicators to read one another’s data buffers without repeatedly calling the standard custom-indicator access functions. Its approach passes a dynamic array’s memory address to a small C++ DLL, then uses that…
The article outlines a foreign-exchange arbitrage prototype that uses Python with MetaTrader 5. It retrieves tick data for multiple currency pairs, removes duplicate timestamps, calculates synthetic prices from combinations of quoted pairs, and compares…
The article demonstrates a workflow for exploring tick-level strategies in MetaTrader 5. It proposes tracking changes between consecutive prices, estimating their standard deviation over a configurable tick window, and marking unusually large moves for…
This article details a practical token-generation stage for a LightGTS-style forecasting model. It first estimates each input series’ dominant frequency with a Fourier transform, then uses that estimate to set patch length and overlap while keeping the…
The article compares MetaTrader 5 and QUIK using three measures: elapsed time for sequential confirmed market orders, time to send a sequence of unconfirmed orders, and the frequency of market-depth updates. The tests were run on the same hosted computer,…